Abstract: Feature engineering is one of the most important and time consuming tasks in
predictive analytics projects. It involves understanding domain knowledge and
data exploration to discover relevant hand-crafted features from raw data. In
this paper, we introduce a system called One Button Machine, or OneBM for
short, which automates feature discovery in relational databases. OneBM
automatically performs a key activity of data scientists, namely, joining of
database tables and applying advanced data transformations to extract useful
features from data. We validated OneBM in Kaggle competitions in which OneBM
achieved performance as good as top 16% to 24% data scientists in three Kaggle
competitions. More importantly, OneBM outperformed the state-of-the-art system
in a Kaggle competition in terms of prediction accuracy and ranking on Kaggle
leaderboard. The results show that OneBM can be useful for both data scientists
and non-experts. It helps data scientists reduce data exploration time allowing
them to try and error many ideas in short time. On the other hand, it enables
non-experts, who are not familiar with data science, to quickly extract value
from their data with a little effort, time and cost.